Converting Multilayer Glosses into Semantic and Pragmatic forms with GENLIS

This paper presents work carried out to transform glosses of a fable in Italian Sign Language (LIS) into a text which is then read by a TTS synthesizer from an SSML modified version of the same text. Whereas many systems exist that generate sign language from a text, we decided to do the reverse operation and generate text from LIS. For that purpose we used a version of the fable The Tortoise and the Hare, signed and made available on Youtube by ALBA cooperativa sociale, which was annotated manually by second author for her master's thesis. In order to achieve our goal, we converted the multilayer glosses into linear Prolog terms to be fed to the generator. In the paper we focus on the main problems encountered in the transformation of the glosses into a semantically and pragmatically consistent representation. The main problems have been caused by the complexities of a text like a fable which requires coreference mechanisms and speech acts to be implemented in the representation which are often unexpressed and constitute implicit information.

Towards Layered Events and Schema Representations in Long Documents

In this thesis proposal, we explore the application of event extraction to literary texts. Considering the lengths of literary documents modeling events in different granularities may be more adequate to extract meaningful information, as individual elements contribute little to the overall semantics. We adapt the concept of schemas as sequences of events all describing a single process, connected through shared participants extending it to for multiple schemas in a document. Segmentation of event sequences into schemas is approached by modeling event sequences, on such task as the narrative cloze task, the prediction of missing events in sequences. We propose building on sequences of event embeddings to form schema embeddings, thereby summarizing sections of documents using a single representation. This approach will allow for the comparisons of different sections of documents and entire literary works. Literature is a challenging domain based on its variety of genres, yet the representation of literary content has received relatively little attention.

Why Do Document-Level Polarity Classifiers Fail?

Machine learning solutions are often criticized for the lack of explanation of their successes and failures. Understanding which instances are misclassified and why is essential to improve the learning process. This work helps to fill this gap by proposing a methodology to characterize, quantify and measure the impact of hard instances in the task of polarity classification of movie reviews. We characterize such instances into two categories: neutrality, where the text does not convey a clear polarity, and discrepancy, where the polarity of the text is the opposite of its true rating. We quantify the number of hard instances in polarity classification of movie reviews and provide empirical evidence about the need to pay attention to such problematic instances, as they are much harder to classify, for both machine and human classifiers. To the best of our knowledge, this is the first systematic analysis of the impact of hard instances in polarity detection from well-formed textual reviews.

Modeling of a Multi-Layers Artificial Neural Networks to estimate the Duty Cycle of DC-DC Boost Converter to track the Maximum Power Point of Photovoltaic Energy Systems

This research deals with the modeling of a Multi-Layers Feed Forward Artificial Neural Networks (MLFFNN), trained using Gradient Descent algorithm with Momentum factor & adaptive learning rate, to estimate the output of the neural network corresponding to the optimal Duty Cycle of DC-DC Boost Converter to track the Maximum Power Point of Photovoltaic Energy Systems. Thus, the DMPPT-ANN “Developed MPPT-ANN” controller proposed in this research, independent in his work on the use of electrical measurements output of PV system to determine the duty cycle, and without the need to use a Proportional-Integrative Controller to control the cycle of the work of the of DC-DC Boost Converter, and this improves the dynamic performance of the proposed controller to determine the optimal Duty Cycle accurately and quickly. In this context, this research discusses the optimal selection of the proposed MLFFNN structure in the research in terms of determining the optimum number of hidden layers and the optimal number of neurons in them, evaluating the values of the Mean square error and the resulting Correlation Coefficient after each training of the neural network. The final network model with the optimal structure is then adopted to form the DMPPT-ANN Controller to track the MPP point of the PV system. The simulation results performed in the Matlab / Simulink environment demonstrated the best performance of the proposed DMPPT-ANN controller based on the MLFFNN neural network model, by accurately estimating the Duty Cycle and improving the response speed of the PV system output to MPP access, , as well as finally eliminating the resulting oscillations in the steady state of the Power response curve of PV system compared with the use of a number of reference controls: an advanced tracking controller MPPT-ANN-PI based on ANN network to estimate MPP point voltage with conventional PI controller, a MPPT-FLC and a conventional MPPT-INC uses the Incremental Conductance technique INC

Numerical Analysis and Model tests of the Bearing Capacity of shallow Strip Footing resting on Multi-layered Soils

In present investigation attempt has been made to study the bearing capacity and settlement characteristics of footings subjected to central vertical load and resting on layered soil with the help of model tests and with the application of finite element method (FEM) to calculate bearing capacity of a strip footing on one-layer and two-layer soil (Sand and Clay). To investigate the effect of various parameters on soil bearing Capacity a commercial finite element software, PLAXIS, has been used. Soil profile contains two soil types including sand and clay. Soil behavior is represented by the elasto-plastic Mohrcoulomb (MC) -model. For a one-layer case, the bearing capacity also is calculated which has a good agreement with theoretical equations. For a layered soil, soft-over strong soil, parametric study was carried out. It is concluded that the bearing capacity of footing decreases as the height of clayey soil increases whilst the displacement under footing increases. There is a critical depth where the stronger bottom layer does not affect ultimate bearing capacity and failure mechanism of footing.

Comparison between AngularJS 1 and Angular 2 in the Implementation of the Presentation Layer of Multitiered Ecommerce Applications

This paper focuses on application built using the Java Platform, Enterprise Edition (Java EE). In this application, the business-tier is based on representational state transfer (RESTful) web services, and the presentation tier adopts Angular(x) framework.

Water Coning Isolating Techniques and their Enhancing in ALRoumailan and ALGbisseh Fields

The Objectives of this research are to study the Oil Formation Covered with Water or Gas, Formation of Water or Gas Coning and Mathematics Control Mechanisms of it, then to know the Water Coning Isolating Types in the Syrian Fields (as ALRoumailan and ALGbisseh).

A Study on Recycling the Bituminous Pavements

studying the recycling of bituminous pavements is important to achieve a set of objectives. The most important one is to examine the asphalt obtained from the recycled bituminous pavements in order to identify its properties and suitability for reuse according to its serviceability, reductions and cost benefit.

Using satellite images in updating topographic maps (An applicated study on Al-Bahlolia district)

The science and art of producing maps had been subjected to the changes as a result of new recent techniques developments at space photogrammetry, that lead to appearance of programs and applications in the computer's world. This associated with the advent of information age and Geographic information system that changed the traditional topographic map from just a map to an analyzing and viewing tool. All Syrian Topographic maps are old, out dated, and largely exist in paper form. Due to the high cost of aerial photography, These maps have not been updated for many years and such are not useful for planning. Therefore, there is an urgent need to produce new maps using high resolution satellite images. The research put a method for updating topographic maps of Al-Bahlolia district which have scales (1/50000) and (1/200000), By using Cartosat1 images. After updating, The results were that there is increasing in the area of planted land. In addition to building developments, increasing of length and density of roads between and inside villages. Contour lines also have been generated automatically, so efforts and time were be saved.

Implementing Multi-Tiered E-commerce Applications and Assessing the Impact of the Different Techniques on Performance

Multitiered ecommerce applications are distributed applications where application logic is divided into components according to function. These components are installed on different machines, depending on the tier to which the application component belongs , additionally, these applications provide ecommerce services like online shopping